基于數(shù)據(jù)挖掘的圖書(shū)館個(gè)性化服務(wù)系統(tǒng)的研究與應(yīng)用

1、學(xué) 位 論 文 獨(dú) 創(chuàng) 性 說(shuō) 明本人鄭重聲明：所呈交的學(xué)位論文是我個(gè)人在導(dǎo)師指導(dǎo)下進(jìn)行的研究工作及其取得研究成果。盡我所知，除了文中加以標(biāo)注和致謝的地方外，論文中不包含其他人或集體已經(jīng)公開(kāi)發(fā)表或撰寫(xiě)過(guò)的研究成果，也不包含為獲得西安科技大學(xué)或其他教育機(jī)構(gòu)的學(xué)位或證書(shū)所使用過(guò)的材料。與我一同工作的同志對(duì)本研究所做的任何貢獻(xiàn)均已在論文中做了明確的說(shuō)明并表示了謝意。學(xué)位論文作者簽名： 日期：ABSRTACTWith the developme

2、nt of information technology, the traditional management and serviceof the library obviously cannot adapt to the growing requirements of the information.So weneed to find the new techniques and methods to improve.The per

3、sonalized service system issurely the trend of library modernization.This paper first describe the current research andsignificance of the library personalized service system,then focuses on the recommendationsystem and

4、decision supporting system.The main contents of this paper are as follows:(1) The main function of the library personalized service system is to find the informationthat the user really care. The recommendation algorithm

5、 is the core of the recommendationsystem.This paper describes several kinds of recommendation algorithms,analyzes theirfeatures and deficiencies, then combine their strengths in a hybrid recommendation algorithm.The algo

6、rithm is applied to the library recommendation system.(2) In the library personalized service system the decision supporting system is theimportant function for the administrator.After analysing all the data and informat

7、ion thedecision supporting system can provide a variety of options.Then by comparing and judgingthe decision supporting system will give the best one.To achieve this,the system not only needsthe multidimensional and mult

8、ilevel association rule algorithm to create rules, but also needsthe data mining technology and OLAP to mine and analyse the data.At last, this paper analyses and designs the library personalized service system.Thesystem

9、 is tested,and the result of the system performance test is rather good just as expected.Key Words: Library personalized service;Recommendation; Decision making technology;Data miningThesis：Application ResearchSubject :